25,853 research outputs found

    Evaluating the impact of physical activity apps and wearables: interdisciplinary review

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    Background: Although many smartphone apps and wearables have been designed to improve physical activity, their rapidly evolving nature and complexity present challenges for evaluating their impact. Traditional methodologies, such as randomized controlled trials (RCTs), can be slow. To keep pace with rapid technological development, evaluations of mobile health technologies must be efficient. Rapid alternative research designs have been proposed, and efficient in-app data collection methods, including in-device sensors and device-generated logs, are available. Along with effectiveness, it is important to measure engagement (ie, users’ interaction and usage behavior) and acceptability (ie, users’ subjective perceptions and experiences) to help explain how and why apps and wearables work. Objectives: This study aimed to (1) explore the extent to which evaluations of physical activity apps and wearables: employ rapid research designs; assess engagement, acceptability, as well as effectiveness; use efficient data collection methods; and (2) describe which dimensions of engagement and acceptability are assessed. Method: An interdisciplinary scoping review using 8 databases from health and computing sciences. Included studies measured physical activity, and evaluated physical activity apps or wearables that provided sensor-based feedback. Results were analyzed using descriptive numerical summaries, chi-square testing, and qualitative thematic analysis. Results: A total of 1829 abstracts were screened, and 858 articles read in full. Of 111 included studies, 61 (55.0%) were published between 2015 and 2017. Most (55.0%, 61/111) were RCTs, and only 2 studies (1.8%) used rapid research designs: 1 single-case design and 1 multiphase optimization strategy. Other research designs included 23 (22.5%) repeated measures designs, 11 (9.9%) nonrandomized group designs, 10 (9.0%) case studies, and 4 (3.6%) observational studies. Less than one-third of the studies (32.0%, 35/111) investigated effectiveness, engagement, and acceptability together. To measure physical activity, most studies (90.1%, 101/111) employed sensors (either in-device [67.6%, 75/111] or external [23.4%, 26/111]). RCTs were more likely to employ external sensors (accelerometers: P=.005). Studies that assessed engagement (52.3%, 58/111) mostly used device-generated logs (91%, 53/58) to measure the frequency, depth, and length of engagement. Studies that assessed acceptability (57.7%, 64/111) most often used questionnaires (64%, 42/64) and/or qualitative methods (53%, 34/64) to explore appreciation, perceived effectiveness and usefulness, satisfaction, intention to continue use, and social acceptability. Some studies (14.4%, 16/111) assessed dimensions more closely related to usability (ie, burden of sensor wear and use, interface complexity, and perceived technical performance). Conclusions: The rapid increase of research into the impact of physical activity apps and wearables means that evaluation guidelines are urgently needed to promote efficiency through the use of rapid research designs, in-device sensors and user-logs to assess effectiveness, engagement, and acceptability. Screening articles was time-consuming because reporting across health and computing sciences lacked standardization. Reporting guidelines are therefore needed to facilitate the synthesis of evidence across disciplines

    Quantifying subjective quality evaluations for mobile video watching in a semi-living lab context

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    This paper discusses results from an exploratory study in which Quality of Experience aspects related to mobile video watching were investigated in a semi-living lab setting. More specifically, we zoom in on usage patterns in a natural research context and on the subjective evaluation of high and low-resolution movie trailers that are transferred to a mobile device using two transmission protocols for video (i.e., real-time transport protocol and progressive download using HTTP). User feedback was collected by means of short questionnaires on the mobile device, combined with traditional pen and paper diaries. The subjective evaluations regarding the general technical quality, perceived distortion, fluentness of the video, and loading speed are studied and the influence of the transmission protocol and video resolution on these evaluations is analyzed. Multinomial logistic regression results in a model to estimate the subjective evaluations regarding the perceived distortion and loading speed based on objectively-measured parameters of the video session

    Fall Prediction and Prevention Systems: Recent Trends, Challenges, and Future Research Directions.

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    Fall prediction is a multifaceted problem that involves complex interactions between physiological, behavioral, and environmental factors. Existing fall detection and prediction systems mainly focus on physiological factors such as gait, vision, and cognition, and do not address the multifactorial nature of falls. In addition, these systems lack efficient user interfaces and feedback for preventing future falls. Recent advances in internet of things (IoT) and mobile technologies offer ample opportunities for integrating contextual information about patient behavior and environment along with physiological health data for predicting falls. This article reviews the state-of-the-art in fall detection and prediction systems. It also describes the challenges, limitations, and future directions in the design and implementation of effective fall prediction and prevention systems

    Assessing quality of experience of IPTV and video on demand services in real-life environments

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    The ever growing bandwidth in access networks, in combination with IPTV and video on demand (VoD) offerings, opens up unlimited possibilities to the users. The operators can no longer compete solely on the number of channels or content and increasingly make high definition channels and quality of experience (QoE) a service differentiator. Currently, the most reliable way of assessing and measuring QoE is conducting subjective experiments, where human observers evaluate a series of short video sequences, using one of the international standardized subjective quality assessment methodologies. Unfortunately, since these subjective experiments need to be conducted in controlled environments and pose limitations on the sequences and overall experiment duration they cannot be used for real-life QoE assessment of IPTV and VoD services. In this article, we propose a novel subjective quality assessment methodology based on full-length movies. Our methodology enables audiovisual quality assessment in the same environments and under the same conditions users typically watch television. Using our new methodology we conducted subjective experiments and compared the outcome with the results from a subjective test conducted using a standardized method. Our findings indicate significant differences in terms of impairment visibility and tolerance and highlight the importance of real-life QoE assessment

    Towards a new ITU-T recommendation for subjective methods evaluating gaming QoE

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    This paper reports on activities in Study Group 12 of the International Telecommunication Union (ITU-T SG12) to define a new Recommendation on subjective evaluation methods for gaming Quality of Experience (QoE). It first resumes the structure and content of the current draft which has been proposed to ITU-T SG12 in September 2014 and then critically discusses potential gaming content and evaluation methods for inclusion into the upcoming Recommendation. The aim is to start a discussion amongst experts on potential evaluation methods and their limitations, before finalizing a Recommendation. Such a recommendation might in the end be applied by non -expert users, hence wrong decisions in the evaluation design could negatively affect gaming QoE throughout the evaluation

    Beyond multimedia adaptation: Quality of experience-aware multi-sensorial media delivery

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    Multiple sensorial media (mulsemedia) combines multiple media elements which engage three or more of human senses, and as most other media content, requires support for delivery over the existing networks. This paper proposes an adaptive mulsemedia framework (ADAMS) for delivering scalable video and sensorial data to users. Unlike existing two-dimensional joint source-channel adaptation solutions for video streaming, the ADAMS framework includes three joint adaptation dimensions: video source, sensorial source, and network optimization. Using an MPEG-7 description scheme, ADAMS recommends the integration of multiple sensorial effects (i.e., haptic, olfaction, air motion, etc.) as metadata into multimedia streams. ADAMS design includes both coarse- and fine-grained adaptation modules on the server side: mulsemedia flow adaptation and packet priority scheduling. Feedback from subjective quality evaluation and network conditions is used to develop the two modules. Subjective evaluation investigated users' enjoyment levels when exposed to mulsemedia and multimedia sequences, respectively and to study users' preference levels of some sensorial effects in the context of mulsemedia sequences with video components at different quality levels. Results of the subjective study inform guidelines for an adaptive strategy that selects the optimal combination for video segments and sensorial data for a given bandwidth constraint and user requirement. User perceptual tests show how ADAMS outperforms existing multimedia delivery solutions in terms of both user perceived quality and user enjoyment during adaptive streaming of various mulsemedia content. In doing so, it highlights the case for tailored, adaptive mulsemedia delivery over traditional multimedia adaptive transport mechanisms
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